Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network

  • Anuj Kumar
Keywords: Classification, Radiology, Machine Learning, Convolution Neural Network, Chest X-Ray images.

Abstract

Chest X-Rays are generally used for diagnosing abnormalities in the thoracic area. Radiologists need to spend significant amount of time for interpreting scans. Automatic classification of these images could greatly help radiology interpretation process by enhancing real world diagnosis of problems. Hence, radiologists can focus on detecting abnormalities from the abnormal images rather than checking for it in all the images. In this paper, we present a machine learning approach to solve this problem. Here, the algorithm uses Convolutional Neural Networks (CNN) to learn and classify chest X-ray images as normal or abnormal based on image features.

References

[1] Alex Krizhevsky, Ilya Sutskever and Geoffrey E. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,”papers.nips:4824, December 03 - 06, 2012.
[2] Jianxin Wu, “Introduction to Convolutional Neural Networks,” National Key Lab for Novel Software Technology Nanjing University, May 1, 2017 cs.nju:wujx.
[3] Dr. Rama Kishore,Taranjit Kaur, “Backpropagation Algorithm: An Artificial Neural Network Approach for Pattern Recognition,” International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June2012: 1ISSN 2229-5518.
[4] Ms. Sonali. B. Maind and Ms. Priyanka Wankar, “Research Paper on Basic of Artificial Neural Network,”International Journal on Recent and Innovation Trends in Computing and Communication,Volume: 2 Issue: 1, January 2014, ISSN: 2321-8169.
[5] Saeed AL-Mansoori, “Intelligent Handwritten Digit Recognition using Artificial Neural Network,” Int. Journal of Engineering Research and Applications, ISSN : 2248-9622, Vol. 5, Issue 5, ( Part -3) May 2015, pp.46-51.
[6] Chen Wang and Yang Xi., “Convolutional Neural Network for Image Classification,” Johns Hopkins University Baltimore, MD 21218, cs.jhu: ~cwang107.
[7] Deepika Jaswal and Sowmya.V, K.P.Soman, “Image Classification Using Convolutional Neural Networks,”International Journal of Scientific & Engineering Research, Volume 5, Issue 6, June-2014 ISSN: 2229-5518.
[8] Yuxi Dong, Yuchao Pan, Jun Zhang and Wei Xu, “Learning to Read Chest X-Ray Images from 16000+ Examples Using CNN,”Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2017 IEEE/ACM International Conference, July 2017, DOI: 10.1109/CHASE.2017.59
[9] A. K. Santra, C. Josephine Christy, “Genetic Algorithm and Confusion Matrix for Document Clustering,”IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No 2, January 2012.
Published
2018-04-15
How to Cite
Kumar, A. (2018, April 15). Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network. ASIAN JOURNAL FOR CONVERGENCE IN TECHNOLOGY (AJCT ) -UGC LISTED, 4(I). Retrieved from http://asianssr.org/index.php/ajct/article/view/454
Section
Electronics and Telecommunication